Reverse shoulder pre-operative planning

ABSTRACT

A method of pre-operatively developing a reverse shoulder arthroplasty plan can include receiving an image of a patient shoulder comprising a humerus and a glenoid. The image can be segmented to develop a 3D shoulder model. Virtual surgery can be performed on the 3D shoulder model to generate a modified shoulder model. The virtual surgery can include resecting and reaming a virtual humerus of the 3D shoulder model, and reaming a virtual glenoid of the 3D shoulder model. Selection of a humeral implant and selection of a glenoid implant can be received. A virtual representation of the humeral implant can be implanted on the virtual humerus and a virtual representation of the glenoid implant on the virtual glenoid to virtually update the modified shoulder model. A range of motion of the patient shoulder can be determined and a reverse shoulder arthroplasty can be finalized based on the range of motion.

CLAIM OF PRIORITY

This application claims the benefit of U.S. Provisional PatentApplication Ser. No. 62/360,140, filed on Jul. 8, 2016, and U.S.Provisional Patent Application Ser. No. 62/476,112, filed on Mar. 24,2017, the benefit of priority of each are claimed hereby, and which areincorporated by reference herein in its entirety.

FIELD

The present subject matter relates to orthopedic procedures and, moreparticularly, to systems and methods that can aid in performing reverseshoulder arthroplasties.

BACKGROUND

The shoulder joint is a complex joint with the scapula, clavicle and thehumerus all coming together to enable a wide range of movement, at leastin a properly functioning joint. In a properly functioning shoulderjoint the head of the humerus fits into a shallow socket in the scapula,typically referred to as the glenoid. Articulation of the shoulder jointinvolves movement of the humeral head in the glenoid, with the structureof the mating surfaces and surrounding tissues providing a wide range ofmotion.

The shoulder joint can undergo degenerative changes caused by variousissues, such as rheumatoid arthritis, osteoarthritis, rotator cuffarthroplasty, vascular necrosis, or bone fracture. When severe jointdamage occurs and no other means of treatment is found to be effective,a total, partial, or reverse shoulder replacement or reconstruction maybe necessary. Reverse shoulder replacements can include a cup shapedarticular surface attached to a stem implanted into the humerus, while aspherical glenoid component is used to provide an articular surface toengage the humeral cup.

OVERVIEW

During shoulder arthroplasty surgery, the components of the prosthesisare matched with the biology of the patient in an effort to maintain orrestore a natural range of motion of a healthy shoulder joint. Patientspecific instrumentation can assist a surgeon in planning andimplementing a shoulder arthroplasty to restore natural movement.However, even with the multitude of advances in prosthetic componentsand patient specific instrumentation, restoring a full range of motioncan remain difficult, especially for a surgeon who does not regularlyperform shoulder replacements. In some cases, range of motion of apatient following a successful procedure is limited more than isdesirable to some patients.

The systems, devices, methods, and instruments discussed herein canprovide virtual calculations and measurements to assist surgeons indetermining whether virtual prosthetic devices may provide a patientwith desirable outcomes. By determining range of motion, conditions ofoperation, and probability of joint functions, a pre-operative plan canbe developed to provide standards of care that more routinely result insuccessful outcomes. Well-formed pre-operative plans can also result inmore successful outcomes over intra-operative selection of prosthesesand installation provisions, such as resection and reaming.

While the above discusses issues and procedures specific to shoulderreplacement procedures, discussion of the following systems, devices,methods, and instruments is also applicable for use in other jointreplacement procedures, such as anatomic total shoulder arthroplasty(aTSA), total hip arthroplasty (THA) or total knee arthroplasty (TKA).Further, the systems, devices, methods, and instruments may also beapplicable to aspects of partial knee replacements and other orthopedicprocedures to repair of joints.

To further illustrate the apparatuses and systems disclosed herein, thefollowing non-limiting examples are provided:

Example 1 is a method of pre-operatively developing a reverse shoulderarthroplasty plan, the method can include: receiving an image of apatient shoulder comprising a humerus and a glenoid; segmenting theimage to develop a 3D shoulder model; performing virtual surgery on the3D shoulder model to generate a modified shoulder model, the virtualsurgery comprising: resecting and reaming a virtual humerus of the 3Dshoulder model; reaming a virtual glenoid of the 3D shoulder model;receiving selection of a humeral implant; receiving selection of aglenoid implant; implanting, virtually to update the modified shouldermodel, a virtual representation of the humeral implant on the virtualhumerus and a virtual representation of the glenoid implant on thevirtual glenoid; determining a range of motion of the patient shoulderbased on analysis of the updated modified shoulder model includingdetermining an expected interaction between the virtual representationof the humerus implant and the virtual representation of the glenoidimplant after the selected virtual humeral implant and the selectedvirtual glenoid implant are virtually implanted; and finalizing areverse shoulder arthroplasty plan when the range of motion is within adesired range and receiving selection of at least one of a secondhumeral implant and a second glenoid implant when the range of motion isnot within the desired range.

In Example 2, the subject matter of Example 1 optionally includesdisplaying on a user interface a graphic representation of the range ofmotion.

In Example 3, the subject matter of Example 2 optionally includesdisplaying on the graphic representation of the range of motion and arange of motion required to perform a common daily activity.

In Example 4, the subject matter of any one or more of Examples 2-3optionally include determining whether the updated modified shouldermodel can perform the common daily activity as a function of the rangeof motion.

In Example 5, the subject matter of any one or more of Examples 2-4optionally include displaying on the graphic representation of the rangeof motion and a range of motion required to perform a second commondaily activity; and determining whether the updated modified shouldermodel can perform the second common daily activity as a function of therange of motion.

In Example 6, the subject matter of any one or more of Examples 2-5optionally include identifying collisions between components of theupdated modified shoulder model; and developing the range of motion as afunction of the identified collisions.

In Example 7, the subject matter of Example 6 optionally includesidentifying areas of collision as a function of the identifiedcollisions; and displaying on the graphic representation of the range ofmotion, the identified areas of collision.

In Example 8, the subject matter of any one or more of Examples 1-7optionally include wherein: the virtual representation of the humeralimplant includes a humeral implant thickness, offset, articulationsurface radius, implant version, and position on the virtual humerus;and the virtual representation of the glenoid implant includes a glenoidimplant thickness, offset, eccentricity, and position on the virtualglenoid.

In Example 9, the subject matter of Example 8 optionally includeswherein receiving selection of the humeral implant includes selectingthe humeral implant from a library of humeral implants as a function ofthe humeral implant thickness, offset, articulation surface radius,implant version, and position on the virtual humerus; and whereinreceiving selection of the glenoid implant includes selecting theglenoid implant from a library of glenoid implants as a function of theglenoid implant thickness, offset, eccentricity, and position on thevirtual glenoid.

In Example 10, the subject matter of Example 9 optionally includesreceiving a thickness adjustment of at least one of the humeral implantand the glenoid implant when the range of motion is not within thedesired range; receiving an offset adjustment of at least one of thehumeral implant relative to the humerus and the glenoid implant relativeto the glenoid when the range of motion is not within the desired range;and receiving a position adjustment of at least one of the humeralimplant on the virtual humerus and the glenoid implant on the virtualglenoid when the range of motion is not within the desired range.

In Example 11, the subject matter of any one or more of Examples 9-10optionally include selecting a base virtual representation of thehumeral implant and a base virtual representation of the glenoid implantas a function of adjusting at least one of thickness, offset, andposition of the virtual representation of the humeral implant and thevirtual representation of the glenoid implant.

In Example 12, the subject matter of Example 11 optionally includesdisplaying a graphic representation on a user interface of a range ofmotion of the updated modified shoulder model including the base virtualrepresentation of the humeral implant and the base virtualrepresentation of the glenoid implant; and adjusting at least one of thebase virtual representation of the humeral implant and the base virtualrepresentation of the glenoid implant using the user interface.

In Example 13, the subject matter of any one or more of Examples 11-12optionally include adjusting the virtual surgery as a function of atleast one of the base virtual humeral implant and a base virtual glenoidimplant.

In Example 14, the subject matter of any one or more of Examples 1-13optionally include determining a probability of one or more of jointloosening, dislocation, laxity, and muscle activation; and adjusting atleast one of the base virtual representation of the humeral implant andthe base virtual representation of the glenoid implant as a function ofthe probability of one or more of joint loosening, dislocation, laxity,and muscle activation.

Example 15 is a method of pre-operatively developing a shoulderarthroplasty plan, the method comprising: receiving an image of apatient shoulder comprising a humerus and a glenoid; segmenting theimage to develop a 3D shoulder model; selecting, based at least in parton the 3D shoulder model, a humeral implant; selecting, base at least inpart on the 3D shoulder model, a glenoid implant; positioning within the3D shoulder model a virtual representation of the humeral implant on thevirtual humerus and a virtual representation of the glenoid implant onthe virtual glenoid; analyzing the 3D shoulder model with the virtualrepresentation of the humeral implant and the virtual representation ofthe glenoid to determine a condition of the patient shoulder includingdetermining an expected interaction between the humerus implant and theglenoid implant; and generating a shoulder arthroplasty plan based atleast in part on the condition.

In Example 16, the subject matter of Example 15 optionally includeswherein the condition is a range of motion of the patient shoulder.

In Example 17, the subject matter of any one or more of Examples 15-16optionally include wherein the analysis includes finite elementanalysis.

In Example 18, the subject matter of Example 17 optionally includeswherein in the condition includes one or more of a humeral force, ahumeral stress, a humeral strain, a glenoid force, a glenoid stress, aglenoid strain, a humeral implant force, a humeral implant stress, ahumeral implant strain, a glenoid implant force, a glenoid implantstress, a glenoid implant strain, a soft tissue force, a soft tissuestress, and a soft tissue strain.

In Example 19, the subject matter of Example 18 optionally includesdisplaying a graphic representation on a user interface of the conditionof the updated modified shoulder model including the virtualrepresentation of the humeral implant and the virtual representation ofthe glenoid implant; and adjusting at least one of the base virtualrepresentation of the humeral implant and the base virtualrepresentation of the glenoid implant using the user interface.

In Example 20, the subject matter of any one or more of Examples 17-19optionally include wherein: the virtual representation of the humeralimplant includes a humeral implant thickness, offset, and position onthe virtual humerus; the virtual representation of the glenoid implantincludes a glenoid implant thickness, offset, and position on thevirtual glenoid; and the selection of one or more of the humeral implantand the glenoid implant can be updated by updating a selection of one ormore of the thickness, offset, and position of the virtualrepresentation of the humeral implant and virtual representation of theglenoid implant.

In Example 21, the subject matter of any one or more of Examples 17-20optionally include aborting an iteration of the finite element analysisof the updated modified shoulder model when one of a maximum humeralforce, a maximum humeral stress, a maximum humeral strain, a glenoidmaximum force, a glenoid maximum stress, a glenoid maximum strain, asoft tissue maximum force, and a soft tissue force minimum force can bedetermined during the finite element analysis.

In Example 22, the subject matter of any one or more of Examples 17-21optionally include wherein the finite element analysis of the updatedmodified shoulder model can be performed on a static model of theupdated modified shoulder model.

In Example 23, the subject matter of any one or more of Examples 17-22optionally include wherein the finite element analysis of the updatedmodified shoulder model can be performed on a dynamic model of theupdated modified shoulder including finite element analysis of theupdated modified shoulder model throughout a range of motion of theupdated modified shoulder model.

Example 24 is a method of pre-operatively developing a reverse shoulderarthroplasty plan, the method comprising: receiving an image of apatient shoulder comprising a humerus and a glenoid; segmenting theimage to develop a 3D shoulder model; performing virtual surgery on the3D shoulder model to generate a modified shoulder model, the virtualsurgery comprising: resecting and reaming a virtual humerus of the 3Dshoulder model; reaming a virtual glenoid of the 3D shoulder model;receiving selection of a humeral implant; receiving selection of aglenoid implant; implanting, virtually to update the modified shouldermodel, a virtual representation of the humeral implant on the virtualhumerus and a virtual representation of the glenoid implant on thevirtual glenoid; determining a range of motion of the patient shoulderbased on analysis of the updated modified shoulder model includingdetermining an expected interaction between the virtual representationof the humerus implant and the virtual representation of the glenoidimplant after the selected virtual humeral implant and the selectedvirtual glenoid implant are virtually implanted; and finalizing areverse shoulder arthroplasty plan when the range of motion is within adesired range and receiving selection of at least one of a secondhumeral implant and a second glenoid implant when the range of motion isnot within the desired range.

In Example 25, the subject matter of Example 24 optionally includesdisplaying on a user interface a graphic representation of the range ofmotion.

In Example 26, the subject matter of any one or more of Examples 24-25optionally include displaying on the graphic representation of the rangeof motion and a range of motion required to perform a common dailyactivity.

In Example 27, the subject matter of any one or more of Examples 24-26optionally include determining whether the updated modified shouldermodel can perform the common daily activity as a function of the rangeof motion.

In Example 28, the subject matter of any one or more of Examples 24-27optionally include displaying on the graphic representation of the rangeof motion and a range of motion required to perform a second commondaily activity; and determining whether the updated modified shouldermodel can perform the second common daily activity as a function of therange of motion.

In Example 29, the subject matter of any one or more of Examples 24-28optionally include identifying collisions between components of theupdated modified shoulder model; and developing the range of motion as afunction of the identified collisions.

In Example 30, the subject matter of any one or more of Examples 24-29optionally include identifying areas of collision as a function of theidentified collisions; and displaying on the graphic representation ofthe range of motion, the identified areas of collision.

In Example 31, the subject matter of any one or more of Examples 24-30optionally include wherein: the virtual representation of the humeralimplant includes a humeral implant thickness, offset, articulationsurface radius, implant version, and position on the virtual humerus;and the virtual representation of the glenoid implant includes a glenoidimplant thickness, offset, eccentricity, and position on the virtualglenoid.

In Example 32, the subject matter of any one or more of Examples 24-31optionally include wherein receiving selection of the humeral implantincludes selecting the humeral implant from a library of humeralimplants as a function of the humeral implant thickness, offset,articulation surface radius, implant version, and position on thevirtual humerus; and wherein receiving selection of the glenoid implantincludes selecting the glenoid implant from a library of glenoidimplants as a function of the glenoid implant thickness, offset,eccentricity, and position on the virtual glenoid.

In Example 33, the subject matter of any one or more of Examples 24-32optionally include receiving a thickness adjustment of at least one ofthe humeral implant and the glenoid implant when the range of motion isnot within the desired range; receiving an offset adjustment of at leastone of the humeral implant relative to the humerus and the glenoidimplant relative to the glenoid when the range of motion is not withinthe desired range; and receiving a position adjustment of at least oneof the humeral implant on the virtual humerus and the glenoid implant onthe virtual glenoid when the range of motion is not within the desiredrange.

In Example 34, the subject matter of any one or more of Examples 24-33optionally include selecting a base virtual representation of thehumeral implant and a base virtual representation of the glenoid implantas a function of adjusting at least one of thickness, offset, andposition of the virtual representation of the humeral implant and thevirtual representation of the glenoid implant.

In Example 35, the subject matter of any one or more of Examples 24-34optionally include displaying a graphic representation on a userinterface of a range of motion of the updated modified shoulder modelincluding the base virtual representation of the humeral implant and thebase virtual representation of the glenoid implant; and adjusting atleast one of the base virtual representation of the humeral implant andthe base virtual representation of the glenoid implant using the userinterface.

In Example 36, the subject matter of any one or more of Examples 24-35optionally include adjusting the virtual surgery as a function of atleast one of the base virtual humeral implant and a base virtual glenoidimplant.

In Example 37, the subject matter of any one or more of Examples 24-36optionally include determining a probability of one or more of jointloosening, dislocation, laxity, and muscle activation; and adjusting atleast one of the base virtual representation of the humeral implant andthe base virtual representation of the glenoid implant as a function ofthe probability of one or more of joint loosening, dislocation, laxity,and muscle activation.

In Example 38, the subject matter of any one or more of Examples 24-37optionally include aborting an iteration of the finite element analysisof the updated modified shoulder model when one of a maximum humeralforce, a maximum humeral stress, a maximum humeral strain, a glenoidmaximum force, a glenoid maximum stress, a glenoid maximum strain, asoft tissue maximum force, and a soft tissue force minimum force can bedetermined during the finite element analysis; and wherein the analysisincludes finite element analysis, and wherein in the condition includesone or more of a humeral force, a humeral stress, a humeral strain, aglenoid force, a glenoid stress, a glenoid strain, a humeral implantforce, a humeral implant stress, a humeral implant strain, a glenoidimplant force, a glenoid implant stress, a glenoid implant strain, asoft tissue force, a soft tissue stress, and a soft tissue strain.

In Example 39, the system, assembly, or method of any one of or anycombination of Examples 1-38 is optionally configured such that allelements or options recited are available to use or select from.

These and other examples and features of the present apparatuses andsystems will be set forth in part in the following Detailed Description.This Overview is intended to provide non-limiting examples of thepresent subject matter—it is not intended to provide an exclusive orexhaustive explanation. The Detailed Description below is included toprovide further information about the present apparatuses and methods.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, which are not necessarily drawn to scale, like numeralscan describe similar components in different views. Like numerals havingdifferent letter suffixes can represent different instances of similarcomponents. The drawings illustrate generally, by way of example, butnot by way of limitation, various examples discussed in the presentdocument.

FIG. 1 illustrates an isometric view of a model of a humerus and scapulaof a patient, in accordance with at least one example of thisdisclosure.

FIG. 2 illustrates a focused view of a model of a humerus and scapula ofa patient, in accordance with at least one example of this disclosure.

FIG. 3 illustrates a schematic view of a method of using the systems ofthe present disclosure, in accordance with at least one example of thisdisclosure.

FIG. 4 illustrates a schematic view of another method of using thesystems of the present disclosure, in accordance with at least oneexample of this disclosure.

FIG. 5 illustrates schematic showing how a system of the presentdisclosure can be connected, in accordance with at least one example ofthis disclosure.

FIG. 6 illustrates a schematic view of another method of using thesystems of the present disclosure, in accordance with at least oneexample of this disclosure.

FIG. 7 illustrates a schematic view of another method of using thesystems of the present disclosure, in accordance with at least oneexample of this disclosure.

FIG. 8 illustrates a chart that can be displayed on a user interface ofthe systems of the present disclosure, in accordance with at least oneexample of this disclosure.

FIG. 9 illustrates a schematic view of another method of using thesystems of the present disclosure, in accordance with at least oneexample of this disclosure.

FIG. 10 illustrates a schematic view of another method of using thesystems of the present disclosure, in accordance with at least oneexample of this disclosure.

FIG. 11 illustrates a schematic view of another method of using thesystems of the present disclosure, in accordance with at least oneexample of this disclosure.

FIG. 12 illustrates a schematic view of another method of using thesystems of the present disclosure, in accordance with at least oneexample of this disclosure.

FIG. 13 illustrates a schematic view of inputs for the methods of thepresent disclosure, in accordance with at least one example of thisdisclosure.

FIG. 14 illustrates a schematic view of another method of using thesystems of the present disclosure, in accordance with at least oneexample of this disclosure.

FIG. 15 illustrates a schematic view of another method of using thesystems of the present disclosure, in accordance with at least oneexample of this disclosure.

FIG. 16 illustrates a schematic view of another method of using thesystems of the present disclosure, in accordance with at least oneexample of this disclosure.

DETAILED DESCRIPTION

The present application relates to devices and systems for shoulderreplacement procedures, such as a reverse shoulder arthroplasty. In someexamples, a virtual surgery can be performed and virtual representationsof implant components can be selected and installed on a virtual modelof a patient's humerus and glenoid. In these examples, a range of motionand/or probable joint operation can be determined and a surgical plancan be developed as a result.

FIG. 1 illustrates an isometric view of model 100, which can includehumerus 102, scapula 104, and implant assembly 106. Humerus 102 caninclude proximal resected portion 110 and distal portion 112.

Model 100 can be a modified model, where the initial model includesmodeled bones created from pre-op images that would not be modified (butwould include representations of the patient's pre-op anatomy, includingany defects). Accordingly, model 100 can be developed from the initialmodel.

Humerus 102 and scapula 104 can be 3D or virtual models of a patient'shumerus and scapula developed from medical images taken pre-operatively.Humerus 102 and scapula 104 can be created based on one or more imagesof a patient's humerus and scapula. The images can be derived from acomputerized tomography (CT) scan, magnetic resonance imaging (MRI),x-ray scan, and the like. The images can be uploaded by a physician (oranother person) to a system, as described further below. Once the imagesare uploaded they can be segmented and tuned to develop the 3D orvirtual model, such as model 100 of FIG. 1.

Humerus 102 can include resected proximal portion 110, which can beconfigured to receive an implant, and can include distal portion 112.Resected proximal potion 110 can be derived from a virtual surgery, asdiscussed below, where a model of a patient's humerus, such as humerus102, can be modified to include a resection. Implant assembly 106 can becomprised of a humeral and a glenoid component, as discussed below,where the humeral implant is implantable into the humerus and theglenoid implant is implantable into the glenoid of scapula 104.

In operation of some examples, the system can receive the images tocreate a virtual 3D model, as described above. Once model 100 iscreated, the system can perform a virtual surgery on humerus 102 andscapula 104 to generate a modified model, such as model 100 shown inFIG. 1. Thereafter, implant assembly 106 can be virtually installed onmodel 100 to create an updated modified model, as shown in FIG. 1. Onceimplant assembly 106 is installed on model 100, the system can be usedto determine whether the updated modified model has a range of motionthat is within a desired range. If the updated modified model has anacceptable range of motion or is deemed otherwise acceptable, a reverseshoulder arthroplasty plan can be finalized by the system. Developing apre-operative plan for an implant assembly that provides a desired rangeof motion can improve the patient's quality of life and can increaseprocedural efficiency. As described below, this analysis can beperformed in several ways.

FIG. 2 illustrates a focused view of a model 100 which can includehumerus 102, scapula 104, and implant assembly 106. Humerus 102 caninclude proximal resected portion 110. Scapula 104 can include glenoid114. Implant assembly 106 can include humeral implant 116 and glenoidimplant 118. Also shown in FIG. 2 are humeral implant offset Oh, glenoidimplant offset Og, center of rotation of glenoid sphere C, glenoidimplant eccentricity Eg, humeral implant articulation radius r, humeralimplant thickness Th, and glenoid thickness Tg.

Glenoid 114 of scapula 104 can be reamed and otherwise prepared toreceive glenoid implant 118. Also, humerus 102 can be resected, reamed,and otherwise prepared to receive humeral implant 116.

Glenoid implant 118 and humeral implant 116 can comprise a reverseshoulder prosthetic assembly for use in a reverse shoulder arthroplasty(configured to be installed in glenoid 114 and resected proximal portion112 of humerus 102). Humeral implant 116 can include a cup having agenerally concave articulating surface configured to interface withglenoid implant 118. Glenoid implant can include a generally convexarticulating surface configured to interface with humeral implant 116.

More specifically, humeral implant 116 can be a body comprised ofmaterials such as plastics (e.g. polyethylene), and/or metal alloys(e.g. titanium alloys, stainless alloys, chromium/cobalt alloys, and thelike) and combinations thereof. Glenoid implant 118 can be a bodycomprised of similar materials, such as plastics and/or metal alloys andcombinations thereof.

Glenoid implant 118 can have a generally smooth convex geometrylaterally facing humerus implant 116. Glenoid implant 118 can have amedial portion coupleable or securable to glenoid 114, such as a stem orother component inserted into a bored or reamed portion of glenoid 114.Glenoid implant 118 can include thickness Tg, which can be a materialthickness partially dictating a distance that glenoid implant 118extends in all directions from glenoid 114. Glenoid implant 118 can alsohave glenoid offset Og, which can be a distance that a center, in someexamples, of glenoid implant 118 is offset from glenoid 114. Glenoidimplant 118 can further include center C, which can be a center ofrotation of the glenoid sphere about the inserted stem. When center C isoffset from a centerline of the glenosphere, it can create a glenoideccentricity Eg. FIG. 2 indicates an inferior glenoid eccentricity,however, glenoid implant 118 can be designed to include glenoideccentricity in any direction. Both center C and glenoid eccentricity Egcan be varied to accommodate a range of motion, as desired and patientanatomy, as can be required.

Humerus implant 116 can have a generally smooth concave geometry definedby articulation surface radius r and medially facing glenoid implant114. Articulation surface radius r can be adjustable to accommodatevariations in range of motion, as required. Humerus implant 116 can havea distal portion coupleable or securable to humerus 102, such as a stemor other component inserted into a bored or reamed portion of resectedproximal portion 112 of humerus 102 and can be inserted at an implantversion to determine rotation of humerus implant 16 relative to aneutral axis of humerus 112 as indicated by the left axis of Oh. Humerusimplant 116 can include thickness Th, which can be a material thicknesspartially dictating a distance that humerus implant 116 extends in alldirections from humerus 102. Humerus implant 116 can also have humerusoffset Oh, which can be a distance that a center, in some examples, ofhumerus implant 116 is offset from a neutral axis of humerus 102.

Also shown in FIG. 2 is contact point 120 (between scapular 104 andhumeral implant 116). Contact point 120 can be used in at least aportion of the calculations to determine a range of motion, as describedfurther below.

FIG. 3 illustrates a schematic view method 300 using the devices andsystems described herein, in accordance with at least one example ofthis disclosure. The steps or operations of method 300 (and of eachmethod discussed herein) are illustrated in a particular order forconvenience and clarity; many of the discussed operations can beperformed in a different sequence or in parallel without materiallyimpacting other operations. Method 300 as discussed includes operationsperformed by multiple different actors, devices, and/or systems. It isunderstood that subsets of the operations discussed in method 300attributable to a single actor, device, or system could be considered aseparate standalone process or method.

At step 302, method 300 can begin with receiving images of a patient'sshoulder, such as from a CT or MRI, for example, as described above.Then, at step 304, the image or images can be segmented to create a 3Dvirtual model of the patient's shoulder. Once the model is developed,virtual surgery can be performed at step 306. The virtual surgery caninclude, for example, resections of bone, such as from the humerus atstep 308. The virtual surgery can also include reaming of the virtualhumerus at step 308 and reaming of the virtual glenoid of the scapulaand at step 310. Other preparations to the bones may also be made atsteps 306, 308, and 310. The virtual surgery can be performed on the 3Dvirtual model of the bones of the joint, in this case the shoulder,within a user interface generated by a computing system for display to asurgeon or physician. The user interface can allow the surgeon toindicate desired implant positions, resections, and/or reaming throughinputs received within the 3D interface. For example, the surgeon may beable to place a resection line or plane relative to a bone or indicatean area of a bone to ream. Alternatively, resections and reaming plansmay be based entirely on virtual implant positioning within the 3Dinterface and can be determined, at least initially, by a systemconsidering prospective implants as well as data or equations used todetermine resection locations and reaming angles. In examples, whererevisions to the bones are based on implant positioning, the revisionsmay be determined at a later operation in method 300.

Thereafter, at step 312, selection of humeral and glenoid components canbe received. The selections can either be received by the system fromanother system, received by the system through a user interface, ordetermined by the system. At step 314, the virtual humeral implant andvirtual glenoid implant can be installed onto the virtual humerus andvirtual glenoid, respectively. The computing system performing orenabling method 300 can generate a user interface to enable the surgeonto select and position the virtual implants in reference to the virtualbones. Method 300 can be continued at method 400, described in FIG. 4below.

FIG. 4 illustrates a schematic view of method 400, which can becontinued from step 314 of method 300 at step 402, where a range ofmotion of the updated modified shoulder model can be determined usingthe 3D model. The range of motion can be determined from an expectedinteraction between the virtual humerus and the virtual glenoid afterthe implants have been installed. The expected interaction can bemodeled using several techniques, some of which are discussed furtherbelow. In some examples, the virtual humerus (including the humeralimplant) can be articulated relative to the glenoid (including theglenoid implant), where rotation is constrained by articulation of thehumeral implant on the glenoid implant. As the humerus is moved througha virtual range of motion it can be noted where impact or a collisionoccurs between the components of the model, such as between the humeralimplant and the scapula. The collisions can be charted or mapped todetermine limitations of rotation of the humerus relative to thescapula.

In some other examples, the range of motion can be determined based onfit analysis. For example, data such as the thickness, offset, andplacement of each insert can be compared to data from previous modelsand/or patients to determine an anticipated range of motion.

At step 404, the range of motion can be displayed on a user interface,such as a monitor or display. In some examples, the range of motion canbe displayed as a graphical display, such as a graphic representation ofa human shoulder. In other examples, a graph or chart can be used todisplay boundaries of the range of motion. In some other examples, therange of motion can be displayed as a list or table of limits.

At step 406, it can be determined whether the range of motion derived instep 402 is of an acceptable range of motion. This decision can bedetermined by a remote system, the system itself, or by a user. In someexamples, the user can utilize the user interface to view the range ofmotion delivered at step 404 to determine whether the range of motion iswithin the desired range of motion. The user can then enter the decisioninto a system at step 406. In some other examples, the system cancompare the range of motion to a typical range of motion of an averagehealthy shoulder. In some other examples, the system can compare therange of motion to one or more ranges of motion required to performdaily activities, as discussed further below. In still other examples,the system can compare specific aspects of the calculated range ofmotion to pre-defined minimally acceptable ranges or thresholds. Forexample, shoulder abduction range needs to minimally reach X, andshoulder adduction range needs to minimally reach Y.

When it is determined that the range of motion is within the desiredrange of motion, a shoulder arthroplasty plan can be finalized at step408. In some examples, this plan can include a written and/or pictoralplan indicating how the humerus and glenoid should be prepared. The plancan also include a detailed description of the humeral and glenoidimplant. Further, the plan can include where the implants should bepositioned relative to the bones and to each other. The plan may alsoinclude other information, such as incision locations, details ondisconnection and reattachment of soft tissues, and the like.

When it is determined that the range of motion is not within the desiredrange of motion, a second humeral implant and/or second glenoid implantcan be selected at step 410. As discussed in later examples, the canalso be an option to reposition the selected implants and/or modify thevirtual surgery. In some examples, the humeral implant and/or theglenoid implant can be selected from a library of glenoid implants and alibrary of humeral implants. In some examples, the library of componentscan be stored in a remote device, such as central device 508 of FIG. 5(discussed below).

The second humeral implant and the second glenoid implant can beinstalled on the virtual humerus and virtual glenoid, respectively, atstep 412, so that a second range of motion can be determined at step 402and so that it can be determined if the second range of motion is withinthe desired range of motion at step 406. In some examples, following oneor more iteration of the steps of method 400, the virtual surgery can bemodified. That is, at least steps 406, 408, and 410 of method 400 can beperformed in an attempt to obtain a desirable range of motion. In someexamples, the virtual surgery can be modified and the implants may notbe reselected and in some examples the virtual surgery can be modifiedand the implants can be re-selected. Steps 402, 406, 410, and 412 can berepeated as necessary until an acceptable range of motion is determined,at which point step 408 can be performed.

Method examples described herein may be machine or computer-implementedat least in part. Some examples may include a computer-readable mediumor machine-readable medium encoded with instructions operable toconfigure an electronic device to perform methods as described in theabove examples. An implementation of such methods may include code, suchas microcode, assembly language code, a higher-level language code, orthe like. Such code may include computer readable instructions forperforming various methods.

The code may form portions of computer program products. Further, in anexample, the code may be tangibly stored on one or more volatile,non-transitory, or non-volatile tangible computer-readable media, suchas during execution or at other times. Examples of these tangiblecomputer-readable media may include, but are not limited to, hard disks,removable magnetic disks, removable optical disks (e.g., compact disksand digital video disks), memory cards or sticks, random access memories(RAMs), read only memories (ROMs), and the like.

FIG. 5 illustrates schematic showing how system 500 can be connected.System 500 can include local device 501, user interface 502, display504, interlink 506, central device 508, central device database 510, andexpert device 512. Local device 501 can include processor 514, volatilememory 516, static memory 518, and network device 520.

Local device 501 can be any computing device, such as a handheldcomputer, for example, a smart phone, a tablet, a laptop, a desktopcomputer, or any other computing device including information processingand storage capabilities and communication capabilities. Local device501 can include processor 514, volatile memory 516, and static memory,which can be connected by wire or other electrical conduit within localdevice 501 and can be configured to receive information, processinformation, output information, and store information. The informationcan be temporarily stored on volatile memory 516 and can be relativelypermanently stored on static memory 518. In some examples,configurations of these components within local device 501 can beconsidered machine readable medium.

The terms “machine readable medium” may include any medium that iscapable of storing, encoding, or carrying instructions for execution bythe device and that cause the device to perform any one or more of thetechniques of the present disclosure, or that is capable of storing,encoding or carrying data structures used by or associated with suchinstructions. Non-limiting machine readable medium examples may includesolid-state memories, and optical and magnetic media. Specific examplesof machine readable media may include: non-volatile memory, such assemiconductor memory devices (e.g., Electrically Programmable Read-OnlyMemory (EPROM), Electrically Erasable Programmable Read-Only Memory(EEPROM)) and flash memory devices; magnetic disks, such as internalhard disks and removable disks; magneto-optical disks; and CD-ROM andDVD-ROM disks.

User interface 502 can be any input and/or output device. For example,user interface can be a monitor, keyboard, and mouse in one example. Inother examples, user interface 502 can be a touch screen display.Display 504 can be a display for displaying output from local device 501and in some examples can receive input and transfer input to localdevice 501 (for example a touch screen display).

Central device 508 can be a remote device similar in configuration tolocal device 501, but located remotely from local device 501. Centraldevice 508 can be configured to connect to multiple of local devices501, in some examples, through interlink 506. Similarly, expert device512 can be a remote device similar in configuration to local device 501,but can be operated by a user considered to be an expert. In operationof some examples, the expert user can interface with the processes anddecisions of the methods discussed herein.

In some examples, user interface and display 504 can be connected tolocal device 501 through wired connections, in some examples (such asUSB, for example), and through wireless connections (such as Bluetooth,for example) in other examples. In some other examples, interlink 506can be a local area network (LAN), wide area network (WAN), and internetprotocol (TCP/IP) connections. Local device 501 can be similarlyconnected to interlink 506 (either through a wired or wirelessconnection). In some examples, network device 520 can connect localdevice 501 to interlink 506. Central device 508, central device database510, and expert device 512 can be connected to interlink 506 in asimilar manner.

In operation of some examples, system 500 can be configured to performsteps of the methods discussed herein and in some examples may performsteps based on a program stored in volatile memory 516 or static memory518, where results of the analysis are stored in either volatile memory516 and/or static memory 518 can be displayed on display 504 and/ortransmitted to user interface 502, central device 508, central devicedatabase 510, and/or expert device 512. For example, system 500 candevelop a reverse shoulder arthroplasty plan by receiving an image of apatient shoulder. One of local device 501, central device 508, andexpert device 512 can segmented the image to develop a 3D shouldermodel.

Then, a device (such as local device 501) can perform virtual surgery onthe 3D shoulder model to generate a modified shoulder model. Themodified shoulder model can be stored in volatile memory 516 and/orstatic memory 518. In some examples, the virtual surgery can includeresecting and reaming a virtual humerus of the 3D shoulder model, andreaming a virtual glenoid of the 3D shoulder model, which can bedisplayed for example, on display 504. Thereafter, selection of ahumeral implant and selection of a glenoid implant can be received froma user interface, such as user interface 502, in some examples, and canbe made by local device in some other examples.

Local device 501, central device 508, or expert device 510 can implant avirtual representation of the humeral implant on the virtual humerus andcan implant a virtual representation of the glenoid implant on thevirtual glenoid to virtually update the modified shoulder model. Theupdated modified shoulder model can be stored in volatile memory 516and/or static memory 518. In some examples, the updated modifiedshoulder model can be stored in central device 508 or expert device 512.One of local device 501, central device 508, and expert device 510 canthen determine a range of motion of the patient shoulder and a reverseshoulder arthroplasty can be finalized based on the range of motion.

Similarly, system 500 can be configured to perform steps of each methoddiscussed herein.

FIG. 6 illustrates a schematic view of method 600, in accordance with atleast one example of this disclosure. At step 602, a range of motion ofthe shoulder can be determined using the 3D model. As discussed at step402, the range of motion can be determined using several techniques.Then, at step 604 daily activities can be selected, where each dailyactivity includes a range of motion. For example, a daily activity suchas combing or brushing hair can be selected, which can include apredetermined approximate range of motion. Other daily activities canalso be used, such as driving a car, stacking dishes on shelves, andopening a door. In some example, more than one daily activity and itsrange of motion can be selected. At step 606, the range of motion can bedisplayed on a user interface, such as a monitor or display. Also, therange of motion of the daily activity or activities can be displayed.

At step 608, it can be determined whether the range of motion derived instep 602 is of an acceptable range of motion. This decision can bedetermined, in some examples, by comparing the range of motion from step602 to the range of motion of the daily activity or activities. In someexamples, this decision can be made by a device of system 500, forexample, and in other examples, this decision can be made by a physicianand/or a patient through a user interface and/or monitor. In someexamples, the user can then enter the decision into a system at step608.

When it is determined that the range of motion is within the desiredrange of motion, a shoulder arthroplasty plan can be finalized at step610. In some examples, this plan can include a written and/or pictoralplan indicating how the humerus and glenoid should be prepared, asdescribed above. This plan can also indicate daily activities for whichthe range of motion has been selected, which can be used to guide andtrack post-operative recovery and therapy.

When it is determined that the range of motion is not within the desiredrange of motion, a second humeral implant and second glenoid implant canbe selected at step 612, which can optionally include adjusting theposition and/or orientation of the implant, as described in furtherdetail below with respect to FIGS. 11 and 12. The second humeral implantand the second glenoid implant can be installed on the virtual humerusand virtual glenoid, respectively, at step 614, so that a second rangeof motion can be determined at step 602 and so that it can be determinedif the second range of motion is within the desired range of motion atstep 608. Steps 602, 604, 606, 608, 612, and 614 can be repeated asnecessary until an acceptable range of motion is determined, at whichpoint step 610 can be performed.

FIG. 7 illustrates a schematic view method 700, in accordance with atleast one example of this disclosure. At step 702, the method can beginby identifying collisions. Collisions can be between implant components,between one implant component and a bone, and between bones. Forexample, a collision can be between a humeral implant and a scapula, asillustrated in FIG. 2 by contact point 120. At step 704, a range ofmotion of the shoulder can be determined by analyzing the collision (asshown in FIG. 8 below), where the outer limits of the range of motionare non-colliding samples or points of analysis.

At step 706, the range of motion can be displayed on a user interface,such as a monitor or display. Also, the collisions and non-collisionpoints can be displayed on the user interface. At step 708, it can bedetermined whether the range of motion derived in step 704 is of anacceptable range of motion. In some examples, this decision can be madeby a device of system 500, for example, and in other examples, thisdecision can be made by a physician and/or a patient through a userinterface and/or monitor. In some examples, collision locations withinthe range of motion can be compared to ranges of motion to performdesired daily activities, and if the collision points will not impededaily activities, the range of motion may be deemed acceptable. The usercan then enter the decision into a system at step 708. In some examples,the range of motion determined by the collisions can be compared withthe range of motion of daily activities (as discussed with reference toFIG. 6).

When it is determined that the range of motion is within the desiredrange of motion, a shoulder arthroplasty plan can be finalized at step710. In some examples, this plan can include a written and/or pictoralplan indicating how the humerus and glenoid should be prepared, asdescribed above.

When it is determined that the range of motion is not within the desiredrange of motion, a second humeral implant and second glenoid implant canbe selected at step 712. The second humeral implant and the secondglenoid implant can be installed on the virtual humerus and virtualglenoid, respectively, at step 714, so that collisions can again bedetermined at step 702 and so that it can be determined if the secondrange of motion is within the desired range of motion at step 708. Steps702, 704, 706, 708, 712, and 714 can be repeated as necessary until anacceptable range of motion is determined, at which point step 710 can beperformed.

FIG. 8 illustrates chart 800 that can be displayed on a user interfaceof the systems of the present disclosure, in accordance with at leastone example of this disclosure.

Chart 800 can include x-axis, y-axis, colliding samples, andnon-colliding samples. Both the x-axis and y-axis can be in units ofdegrees. In some examples, the x-axis can represent flexion andextension and the y-axis can represent adduction and abduction.Colliding samples can be denoted by an asterisk (*) and non-collidingsamples can be denoted by a triangle (▴).

Chart 800 can represent collision samples for a single combination of avirtual surgery and implant selection. In examples where either thevirtual surgery is changed and/or the implant or implants are changed,another chart can be produced. In each chart, samples can be collectedat incremental positions of flexion/extension and adduction/abduction.In some examples, samples can be collected or calculated at incrementsof 10 degrees. In other examples, samples can be calculated atincrements of 1, 2, 3, 4, 5, 6, 8, or 12 degrees.

In some examples, a small increment may be used near a point where acollision has been detected to provide a more precise limit of the rangeof motion. For example, as shown in FIG. 8, a collision was detected at−50 degrees of extension and −80 degrees of abduction. Accordingly,samples of non-collisions were located at −50 degrees of extension and−79 degrees of abduction and at −50 degrees of extension and −78 degreesof abduction. Similarly, relatively small increments may be used alongthe x-axis near a limit of a range of motion, such as between −50 and−40 degrees of extension around −79 degrees of abduction, as shown inFIG. 8.

Once a range of motion has been analyzed, a boundary or limit of therange of motion will be determined as all of the points betweencollision and no collision samples. In the example of FIG. 8, the limitsare displayed as a dense collection of non-colliding samples adjacent acollision area or a dense collection of colliding samples, both of whichcan form lines or curves. A chart displaying limits of the range ofmotion, such as the chart of FIG. 8, can be displayed using a display oruser interface, as described in FIG. 7. Alternatively, the chart can bestored in a matrix or table to be analyzed at a later time.

In either case, the limits of the range of motion can be used todetermine whether a range of motion is within a desired range of motion.In some examples, the chart displaying collisions can be overlaid toshow daily activity range of motion curve using a different color orindicator, such as a plus sign (+) (not shown in FIG. 8). In theseexamples, the chart showing the range of motion as determined usingcollision samples and showing the range of motion of one or more dailyactivities can be outputted to a display or user interface. A physicianand/or a patient can then view the chart to determine whether the rangeof motion is within a desired range of motion.

FIG. 9 illustrates a schematic view of method 900, in accordance with atleast one example of this disclosure. Method 900 can begin at step 902,in some examples, where the humeral implant can be selected. The humeralimplant can be selected to have a particular thickness, offset, implantversion, articulation surface radius, and position, as shown in FIG. 9and as discussed with reference to FIG. 2 above. Similarly, method 900can begin at step 904, in some examples, where the glenoid implant canbe selected. The glenoid implant can be selected to have a particularthickness, offset, glenosphere eccentricity, and position, as shown inFIG. 9 and as discussed above. Once either step 902 or step 904 has beenperformed, the other can be performed.

Once both of steps 902 and 904 have been performed, a range of motioncan be determined at step 906. In some examples, only one of steps 902and 904 can be performed, such as during the second iteration ofselecting a base component. The range of motion can be determined usingone of the several methods discussed above. Then, at step 908, it can bedetermined whether the range of motion is within a desired range ofmotion. This determination can be performed by a system, such as system500, in some examples. When it is determined that the range of motion iswithin the desired range of motion, a base humeral implant and a baseglenoid implant can be determined at step 910.

When it is determined that the range of motion is not within the desiredrange of motion, a second humeral implant and/or second glenoid implantcan be selected at steps 902 and 904. Thereafter, a second range ofmotion can be determined at step 906 and it can be determined if thesecond range of motion is within the desired range of motion at step908. Steps 902, 904, 906, and 908 can be repeated as necessary until anacceptable range of motion is determined, at which point step 910 can beperformed.

FIG. 10 illustrates a schematic view of method 1000, in accordance withat least one example of this disclosure. Method 1000 can begin at step1002, following step 910 of method 900, where a base humeral implant andbase glenoid implant can be selected. The base selections can be made asa function of range of motions determined to be within an acceptablerange in one of the methods previously discussed. Thereafter, at step1004, the operations of the joint may be determined to be at acalculated probability. For example, it can be determined, based on thecalculated range of motion, a probability of dislocation of thepatient's shoulder. In some other examples, a likelihood of jointloosening, joint stability or laxity, or a probability of muscleactivation can be determined.

At step 1006, the probable operations of the joint can be displayed on auser interface. At step 1008, it can be determined whether the probableoperations of the joint are acceptable. In some examples, this decisioncan be made by a device of system 500, for example, and in otherexamples, this decision can be made by a physician and/or a patientthrough a user interface and/or monitor. The user can then enter thedecision into a system at step 1008.

When it is determined that the probable operations of the joint areacceptable, a shoulder arthroplasty plan can be finalized at step 1010.In some examples, this plan can include a written and/or pictoral planindicating how the humerus and glenoid should be prepared, as describedabove.

When it is determined that the probable operations of the joint are notacceptable, the virtual surgery can be adjusted at step 1012. This caninclude modification of resections, connection points of tissues,modifications to reaming, and other aspects of a virtual surgery,discussed in FIG. 3. Further, method 900 can be performed prior to step1002, where a base humeral implant is reselected as a function of theupdated virtual surgery. The second base humeral implant and the secondbase glenoid implant can be installed on the virtual humerus and virtualglenoid, respectively, so that the probable operations of the joint withthe second base implants and the adjusted virtual surgery plan can bedetermined. Steps 1002, 1004, 1006, 1008, and 1012, can be repeated asnecessary until the probable operations of the joint are acceptable, atwhich point step 1010 can be performed.

Though adjusting the virtual surgery is only discussed with respect tomethod 1000, the virtual surgery can be adjusted within each of themethods described above. Additionally, analysis of a virtual jointoperation to determine probable operations of the joint discussed abovecan be introduced into any of the methods discussed herein as anadditional criteria for judging the virtual surgical plan.

FIG. 11 illustrates a schematic view of method 1100 using the devicesand systems described herein, in accordance with at least one example ofthis disclosure. In this example, method 1100 can facilitate selectionand preliminary analysis implant as first steps towards determining afinal shoulder arthroplasty plan. At step 1102, method 1100 can beginwith receiving images of a patient's shoulder, such as from a CT or MRI,for example, as described above. Then, at step 1104, the image or imagescan be segmented to create a 3D virtual model of the patient's shoulder,such as model 100 of FIGS. 1 and 2. Once the model is developed,selection of humeral and glenoid components can be received at step1106. The selections can be received by the system from another system,received by the system through a user interface, and/or determined bythe system through analysis of the 3D virtual model. At step 1108, thevirtual humeral implant and virtual glenoid implant, such as humeral andglenoid components 116 and 118 of FIG. 1, can be positioned relative tovirtual humerus 102 and virtual glenoid 104, respectively.

In some examples, the computing system, such as system 500, performingor enabling method 1100 can generate a user interface to enable thesurgeon to select and position the virtual implants in reference to thevirtual bones. In other examples, the initial placement or positioningof the implants can be determined using an algorithm to place theimplants relative to the virtual humerus and virtual glenoid. In someexamples, the algorithm may include positioning models designed to be agood fit for an average patient. In other examples, the algorithm caninclude methods tailoring initial placement as a function of thepatient's anatomy, such as dimensions of the humerus and glenoid (andtherefore scapula). In some examples, automatic placement can beperformed using an algorithm defined by literature or developed throughtesting and research.

In some cases, the model used for analysis, such as finite elementanalysis (FEA), can be performed using system 500 to adjust the model tomatch anatomy of the patient at step 1110. For example, soft tissueconnection points of the FEA model can be adjusted to match that of theanatomy of the patient. Further, in some examples, humerus and scapulashapes and sizes can be adjusted to match the anatomy of the patient.Once the FEA model has been updated, method 1100 can be continued atstep 1112, where analysis can be performed, as described in furtherdetail in the FIGS. below.

FIG. 12 illustrates a schematic view of method 1200, which can becontinued from step 1112 of method 1100 at step 1202, where analysis canbe performed on the model. In some examples, FEA can be performed on themodel at step 1202 to determine a condition as an output of the model atstep 1204. The condition determined can be a force, stress, strain,range of motion, or other condition of one or more components of themodel, such as a bone, soft tissue, or implant, as discussed in detailfurther below. These conditions can be used to determine whether a modelis desirable, that is, if the model when incorporated into anarthroplasty surgical plan is likely to produce acceptable resultsfollowing the procedure.

At step 1206, the condition can be displayed on user interface 502, suchas a monitor or on display 504. In some examples, the condition can bedisplayed as a graphical display, such as a graphic representation of ahuman shoulder with an indication of the component and its condition. Inother examples, a graph or chart can be used to display the condition.In some other examples, the condition or conditions can be displayed asa list or table of limits.

At step 1208 it can be determined whether the condition is acceptable.For example, it can be determined whether a force on the humerus iswithin an acceptable range. Other conditions can be determined in someexamples, as discussed further below. In some examples, step 1208 caninclude determination of acceptability of multiple conditions. When itis determined that the condition or conditions is/are acceptable, ashoulder arthroplasty plan can be finalized at step 1210. In someexamples, the arthroplasty plan can include a written and/or pictoralplan indicating how the humerus and glenoid should be prepared. This caninclude, for example, locations and angles of resections and positionsand angles of reams. In some examples, the plan can include selection ordevelopment of patient specific cut guides or other instruments that canbe used inter-operatively to replicate the pre-operative plan duringsurgery.

When it is determined that condition is not acceptable, the implantselection can be updated at step 1212, which can include selection of asecond humeral implant and/or a second glenoid implant. Thereafter, atstep 1214, placement of the second humeral implant and/or the secondglenoid implant can be determined. The placement can be determined as afunction of the analysis of steps 1204 and 1208, in some examples. Oncethe implant selection and placement have been updated, the model can beupdated at step 1216, which can include updating soft tissue connectiontension and muscle connections points.

In some examples, the same implants may be used (that is, step 1212 canbe skipped) and the position of the humeral implant and/or the glenoidimplant can be adjusted. For example, reselection of the implants can beskipped if the condition falls just outside of an acceptable range. Insome examples, step 1212 can be skipped, for example, when the analysisof steps 1204 and 1208 indicates that reselection of the implants is notnecessary. In lieu of reselection of the implants, the positions of thepreviously selected implants can be adjusted within the virtual model,which may change how the applicable bones are resected.

After the glenoid implant and humeral implant are virtuallyrepositioned, analysis can be performed again at step 1202. Steps 1202,1204, 1206, 1208, 1210, 1212, and 1214 can be repeated as necessaryuntil an acceptable condition is determined, at which point step 1210can be performed.

FIG. 13 illustrates a schematic view of inputs for the methods describedherein, in accordance with at least one example of this disclosure. Themethod shown in FIG. 13 illustrates how condition 1300 can includevarious inputs that led to calculations or analyses of many components.For example, force 1302, stress 1304, or strain 1306 can be determinedfor each or all of humerus 1308 (which can be humerus 102), scapula orglenoid 1310 (which can be scapula 104 or glenoid 114), soft tissue 1312(for example, a deltoid, transverse humeral ligament, etc.), humeralimplant 1316 (which can be humeral implant 116), or glenoid implant 1318(which can be glenoid implant 118). For example, a glenoid implant forcecan be condition 1300. In other examples, a soft tissue stress can becondition 1300. In some examples, a glenoid implant force and a humeralimplant force can be condition 1300.

In some other examples, range of motion 1318 can be condition 1300. Forexample, a range of motion can be determined via FEA as condition 1300.In some of these examples, the range of motion can be compared to anacceptable range of motion as described with respect to FIGS. 1-10above. Condition 1300 is not limited to those shown in FIG. 13. Forexample, additional qualities or conditions of soft tissue 1312 can beused as condition 1300, such as tension of soft tissues. In each exampleof condition 1300, the condition can be used in the methods describedherein to determine the desirability or acceptability of the virtualmodel.

FIG. 14 illustrates a schematic view of method 1400 using the devicesand systems described herein, in accordance with at least one example ofthis disclosure. FIG. 14 illustrates some examples of how condition 1300of FIG. 13 can be used.

For example, at step 1401 it can be determined whether condition 1300 isacceptable by comparing condition 1300 to condition limits. Each of maxforce 1402, max stress 1404, and max strain 1406 can be values for eachor all of humerus 1408, glenoid 1410, soft tissue 1412, humeral implant1414, and glenoid implant 1416. For example, at step 1401 condition 1300can be compared to max force 1402 of glenoid implant 1416, wherecondition 1300 can be force 1302 of glenoid implant 1316 of FIG. 13.That is, the max force allowable for a glenoid implant can be comparedto the force of the glenoid implant as determined via FEA. In thisexample, it can be determined whether the force of the glenoid implantderived from FEA is lower than the max glenoid implant force.

The condition limits of elements 1402-1416 are not limited to maximumvalues. In some examples, minimum values may be used. For example, aminimum force of soft tissue 1412 may be used to determine minimumlaxity of the virtual shoulder joint. In some examples, muscle and softtissue elongation rates can be considered and the modulus of elasticityof the soft tissues can be considered in some other examples. Though insome cases only one condition may be examined, multiple conditions canbe used in other examples.

When it is determined at step 1401 that condition 1300 is acceptable, orthat condition 1300 is within the range of the limit derived fromelements 1402-1416, the iteration of FEA can be continued at step 1418.Thereafter, in some examples, another of condition 1300 can be derivedfrom FEA, in which case step 1401 can be again performed. In othercases, the iteration can be complete, and a plan can be finalized, suchas in step 1210 of method 1200. When it is determined at step 1401 thatcondition 1300 is unacceptable, or that condition 1300 is not within therange of the limit derived from elements 1402-1416, the iteration of FEAcan be aborted at step 1420. Thereafter, the model can be adjusted atstep 1422 so that a modified model can be analyzed at step 1424 toproduce a new condition at condition 1300. In some examples, models canbe modified and analyzed until condition 1300 is determined to beacceptable. Thereafter, the same model can produce a differentcondition, which can thereafter be analyzed at step 1401. This iterativeprocess can continue until all of the conditions of a model are analyzedand/or deemed acceptable.

FIG. 15 illustrates a schematic view of method 1500, in accordance withat least one example of this disclosure. In the example illustrated,method 1500 shows how various attributes or characteristics can beiteratively selected for when choosing humeral and glenoid implants.

Method 1500 can begin at step 1502, in some examples, where the humeralimplant can be selected. The humeral implant can be selected to have aparticular thickness, offset, and position, as shown in FIG. 15.Similarly, method 1500 can begin at step 1504, in some examples, wherethe glenoid implant can be selected. The glenoid implant can be selectedto have a particular thickness, offset, and position, as shown in FIG.15. Once either step 1502 or step 1504 has been performed, the other canbe performed.

Once both of steps 1502 and 1504 have been performed, a condition can bedetermined at step 1506. In some examples, only one of steps 1502 and1504 can be performed, such as during the second iteration of selectinga base component. The condition can be determined using one of theseveral methods discussed above at step 1508. In some examples, step1508 can include the entire method of method 1400. When it is determinedthat the condition is acceptable, a humeral implant and a glenoidimplant can be finalized and outputted at step 1510. For example, theoutput can be received by system 500 and used in another method of thepresent disclosure, such as method 11, where the entirety of method 15is used to select implants at step 1108. This can be one method ofselecting a set of base implants.

When it is determined that the condition is not acceptable, a secondhumeral implant and/or second glenoid implant can be selected at steps1502 and 1504. Thereafter, a second condition can be determined at step1506 and it can be determined if the second condition is acceptable atstep 1508. Steps 1502, 1504, 1506, and 1508 can be repeated as necessaryuntil a condition is acceptable, at which point step 1510 can beperformed.

FIG. 16 illustrates a schematic view of method 1600, which can begin atstep 1602, where a first condition is selected, which can be a conditionor a position, for example, of humerus 102 relative to scapula 104 orglenoid 114. For example, a first interaction condition may be at aneutral position of the humerus relative to the scapula. Analysis, suchas FEA, can then be performed at step 1604 on a model includingpreviously selected implant components (such as in methods 1100 or1500). The condition can then be outputted from the model at step 1606and displayed at step 1608.

At step 1610 it can be determined whether the condition is acceptable.For example, it can be determined whether a force on the humerus iswithin an acceptable range. In some examples, this decision can be madeby a system using, for example, a method similar to that of method 1400.In some other examples, or after a system has completed analysis, a usersuch as a physician, can determine whether the condition is acceptableat step 1600. The system or user can then make adjustments to the modelat steps 1612 and 1614, where changes to conditions can be seen by theuser at step 1608. In this way, a user can interact with the model tooptimize the model and plan based on the experience of the user.

When it is determined that the condition is not acceptable, the implantselection can be updated at step 1612, which can include selection of asecond humeral implant and/or a second glenoid implant. Thereafter, atstep 1614, placement of the second humeral implant and/or the secondglenoid implant can be determined. The placement can be determined as afunction of the analysis of steps 1604, 1608, and 1610, in someexamples.

When it is determined that the condition is acceptable at step 1610, itcan then be determined whether the iteration was the final iteration inthe range of motion at step 1616. This can be done, in some examples, bycomparing the position of the humerus relative to the glenoid to a listor table of positions requiring analysis. When the range of motion isnot the final iteration of the range of motion, a subsequent positioncan be selected at step 1602. Steps 1602, 1604, 1606, 1608, 1610, 1612,1614, and 1616 can be performed until a full range of motion has beenanalyzed and all of the conditions at each position within the range ofmotion are determined to be acceptable. Once an entire range of motionhas been analyzed and all of the conditions are determined to beacceptable, a shoulder arthroplasty plan can be finalized at step 1618.

In some examples, steps 1612 and steps 1614 can be skipped or repeatedlyskipped such that conditions of an entire range of motion can beanalyzed to determine a set of conditions of the model through theentire range of motion.

Thereafter, the set of conditions can be analyzed to determine if eachcondition is acceptable, allowing for review of all of the conditions ofan entire model. In some examples, multiple models can be analyzed andsteps 1612 and 1614 can be performed between model selections. In thisway, a single model can be selected as a best choice from a set ofanalyzed models.

Additional Notes

The above detailed description includes references to the accompanyingdrawings, which form a part of the detailed description. The drawingsshow, by way of illustration, specific embodiments in which theinvention can be practiced. These embodiments are also referred toherein as “examples.” Such examples can include elements in addition tothose shown or described. However, the present inventors alsocontemplate examples in which only those elements shown or described areprovided. Moreover, the present inventors also contemplate examplesusing any combination or permutation of those elements shown ordescribed (or one or more aspects thereof), either with respect to aparticular example (or one or more aspects thereof), or with respect toother examples (or one or more aspects thereof) shown or describedherein.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one, independent of any otherinstances or usages of “at least one” or “one or more.” In thisdocument, the term “or” is used to refer to a nonexclusive or, such that“A or B” includes “A but not B,” “B but not A,” and “A and B,” unlessotherwise indicated. In this document, the terms “including” and “inwhich” are used as the plain-English equivalents of the respective terms“comprising” and “wherein.” Also, in the following claims, the terms“including” and “comprising” are open-ended, that is, a system, device,article, composition, formulation, or process that includes elements inaddition to those listed after such a term in a claim are still deemedto fall within the scope of that claim. Moreover, in the followingclaims, the terms “first,” “second,” and “third,” etc. are used merelyas labels, and are not intended to impose numerical requirements ontheir objects.

The above description is intended to be illustrative, and notrestrictive. For example, the above-described examples (or one or moreaspects thereof) can be used in combination with each other. Otherexamples can be used, such as by one of ordinary skill in the art uponreviewing the above description. The Abstract is provided to comply with37 C.F.R. §1.72(b), to allow the reader to quickly ascertain the natureof the technical disclosure. It is submitted with the understanding thatit will not be used to interpret or limit the scope or meaning of theclaims. Also, in the above detailed description, various features can begrouped together to streamline the disclosure. This should not beinterpreted as intending that an unclaimed disclosed feature isessential to any claim. Rather, inventive subject matter can lie in lessthan all features of a particular disclosed example. Thus, the followingclaims are hereby incorporated into the detailed description as examplesor embodiments, with each claim standing on its own as a separateexample, and it is contemplated that such examples can be combined witheach other in various combinations or permutations. The scope of theinvention should be determined with reference to the appended claims,along with the full scope of equivalents to which such claims areentitled.

1. A method of pre-operatively developing a reverse shoulderarthroplasty plan, the method comprising: receiving an image of apatient shoulder comprising a humerus and a glenoid; segmenting theimage to develop a 3D shoulder model; performing virtual surgery on the3D shoulder model to generate a modified shoulder model, the virtualsurgery comprising: resecting and reaming a virtual humerus of the 3Dshoulder model; reaming a virtual glenoid of the 3D shoulder model;receiving selection of a humeral implant; receiving selection of aglenoid implant; implanting, virtually to update the modified shouldermodel, a virtual representation of the humeral implant on the virtualhumerus and a virtual representation of the glenoid implant on thevirtual glenoid; determining a range of motion of the patient shoulderbased on analysis of the updated modified shoulder model includingdetermining an expected interaction between the virtual representationof the humerus implant and the virtual representation of the glenoidimplant after the selected virtual humeral implant and the selectedvirtual glenoid implant are virtually implanted; and finalizing areverse shoulder arthroplasty plan when the range of motion is within adesired range and receiving selection of at least one of a secondhumeral implant and a second glenoid implant when the range of motion isnot within the desired range.
 2. The method of claim 1, furthercomprising: displaying on a user interface a graphic representation ofthe range of motion.
 3. The method of claim 2, further comprising:displaying on the graphic representation of the range of motion and arange of motion required to perform a common daily activity.
 4. Themethod of claim 2, further comprising: determining whether the updatedmodified shoulder model can perform the common daily activity as afunction of the range of motion.
 5. The method of claim 2, furthercomprising: displaying on the graphic representation of the range ofmotion and a range of motion required to perform a second common dailyactivity; and determining whether the updated modified shoulder modelcan perform the second common daily activity as a function of the rangeof motion.
 6. The method of claim 2, further comprising: identifyingcollisions between components of the updated modified shoulder model;and developing the range of motion as a function of the identifiedcollisions.
 7. The method of claim 6, further comprising: identifyingareas of collision as a function of the identified collisions; anddisplaying on the graphic representation of the range of motion, theidentified areas of collision.
 8. The method of claim 1, wherein: thevirtual representation of the humeral implant includes a humeral implantthickness, offset, articulation surface radius, implant version, andposition on the virtual humerus; and the virtual representation of theglenoid implant includes a glenoid implant thickness, offset,eccentricity, and position on the virtual glenoid.
 9. The method ofclaim 8, wherein receiving selection of the humeral implant includesselecting the humeral implant from a library of humeral implants as afunction of the humeral implant thickness, offset, articulation surfaceradius, implant version, and position on the virtual humerus; andwherein receiving selection of the glenoid implant includes selectingthe glenoid implant from a library of glenoid implants as a function ofthe glenoid implant thickness, offset, eccentricity, and position on thevirtual glenoid.
 10. The method of claim 9, further comprising:receiving a thickness adjustment of at least one of the humeral implantand the glenoid implant when the range of motion is not within thedesired range; receiving an offset adjustment of at least one of thehumeral implant relative to the humerus and the glenoid implant relativeto the glenoid when the range of motion is not within the desired range;and receiving a position adjustment of at least one of the humeralimplant on the virtual humerus and the glenoid implant on the virtualglenoid when the range of motion is not within the desired range. 11.The method of claim 9, further comprising: selecting a base virtualrepresentation of the humeral implant and a base virtual representationof the glenoid implant as a function of adjusting at least one ofthickness, offset, and position of the virtual representation of thehumeral implant and the virtual representation of the glenoid implant.12. The method of claim 11, further comprising: displaying a graphicrepresentation on a user interface of a range of motion of the updatedmodified shoulder model including the base virtual representation of thehumeral implant and the base virtual representation of the glenoidimplant; and adjusting at least one of the base virtual representationof the humeral implant and the base virtual representation of theglenoid implant using the user interface.
 13. The method of claim 11,further comprising: adjusting the virtual surgery as a function of atleast one of the base virtual humeral implant and a base virtual glenoidimplant.
 14. The method of claim 1, further comprising: determining aprobability of one or more of joint loosening, dislocation, laxity, andmuscle activation; and adjusting at least one of the base virtualrepresentation of the humeral implant and the base virtualrepresentation of the glenoid implant as a function of the probabilityof one or more of joint loosening, dislocation, laxity, and muscleactivation.
 15. A method of pre-operatively developing a shoulderarthroplasty plan, the method comprising: receiving an image of apatient shoulder comprising a humerus and a glenoid; segmenting theimage to develop a 3D shoulder model; selecting, based at least in parton the 3D shoulder model, a humeral implant; selecting, base at least inpart on the 3D shoulder model, a glenoid implant; positioning within the3D shoulder model a virtual representation of the humeral implant on thevirtual humerus and a virtual representation of the glenoid implant onthe virtual glenoid; analyzing the 3D shoulder model with the virtualrepresentation of the humeral implant and the virtual representation ofthe glenoid to determine a condition of the patient shoulder includingdetermining an expected interaction between the humerus implant and theglenoid implant; and generating a shoulder arthroplasty plan based atleast in part on the condition.
 16. The method of claim 15, wherein thecondition is a range of motion of the patient shoulder.
 17. The methodof claim 15, wherein the analysis includes finite element analysis. 18.The method of claim 17, wherein in the condition includes one or more ofa humeral force, a humeral stress, a humeral strain, a glenoid force, aglenoid stress, a glenoid strain, a humeral implant force, a humeralimplant stress, a humeral implant strain, a glenoid implant force, aglenoid implant stress, a glenoid implant strain, a soft tissue force, asoft tissue stress, and a soft tissue strain.
 19. The method of claim18, further comprising: displaying a graphic representation on a userinterface of the condition of the updated modified shoulder modelincluding the virtual representation of the humeral implant and thevirtual representation of the glenoid implant; and adjusting at leastone of the base virtual representation of the humeral implant and thebase virtual representation of the glenoid implant using the userinterface.
 20. The method of claim 17, wherein: the virtualrepresentation of the humeral implant includes a humeral implantthickness, offset, and position on the virtual humerus; the virtualrepresentation of the glenoid implant includes a glenoid implantthickness, offset, and position on the virtual glenoid; and theselection of one or more of the humeral implant and the glenoid implantis updated by updating a selection of one or more of the thickness,offset, and position of the virtual representation of the humeralimplant and virtual representation of the glenoid implant.
 21. Themethod of claim 17, further comprising: aborting an iteration of thefinite element analysis of the updated modified shoulder model when oneof a maximum humeral force, a maximum humeral stress, a maximum humeralstrain, a glenoid maximum force, a glenoid maximum stress, a glenoidmaximum strain, a soft tissue maximum force, and a soft tissue forceminimum force is determined during the finite element analysis.
 22. Themethod of claim 17, wherein the finite element analysis of the updatedmodified shoulder model is performed on a static model of the updatedmodified shoulder model.
 23. The method of claim 17, wherein the finiteelement analysis of the updated modified shoulder model is performed ona dynamic model of the updated modified shoulder including finiteelement analysis of the updated modified shoulder model throughout arange of motion of the updated modified shoulder model.